Detecting code alteration based on memory allocation
Techniques are described for identifying potential code injection attacks against a process by analyzing the memory allocation for the process. Memory allocation data may be collected on one or more host computing devices, the memory allocation data describing the amount of memory allocated for a pr...
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| creator | BREZINSKI DOMINIQUE IMJYA |
| description | Techniques are described for identifying potential code injection attacks against a process by analyzing the memory allocation for the process. Memory allocation data may be collected on one or more host computing devices, the memory allocation data describing the amount of memory allocated for a process or utilized by a process during its execution. The collected memory allocation data may be analyzed to identify instances of anomalous memory allocation during process execution. Statistical or machine learning algorithms may be employed to identify anomalous memory allocation based on the analysis of aggregated memory allocation data for the process. |
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Memory allocation data may be collected on one or more host computing devices, the memory allocation data describing the amount of memory allocated for a process or utilized by a process during its execution. The collected memory allocation data may be analyzed to identify instances of anomalous memory allocation during process execution. 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Memory allocation data may be collected on one or more host computing devices, the memory allocation data describing the amount of memory allocated for a process or utilized by a process during its execution. The collected memory allocation data may be analyzed to identify instances of anomalous memory allocation during process execution. Statistical or machine learning algorithms may be employed to identify anomalous memory allocation based on the analysis of aggregated memory allocation data for the process.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2016</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZDBxSS1JTS7JzEtXSM5PSVVIzClJLUosyczPU0hKLE5NUQAyclNz84sqgVI5-clgKR4G1rTEnOJUXijNzaDg5hri7KGbWpAfn1pckJicmpdaEh8abGlsYmFuYuRkaEyEEgDmMiy1</recordid><startdate>20160524</startdate><enddate>20160524</enddate><creator>BREZINSKI DOMINIQUE IMJYA</creator><scope>EVB</scope></search><sort><creationdate>20160524</creationdate><title>Detecting code alteration based on memory allocation</title><author>BREZINSKI DOMINIQUE IMJYA</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US9348742B13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2016</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>BREZINSKI DOMINIQUE IMJYA</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>BREZINSKI DOMINIQUE IMJYA</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Detecting code alteration based on memory allocation</title><date>2016-05-24</date><risdate>2016</risdate><abstract>Techniques are described for identifying potential code injection attacks against a process by analyzing the memory allocation for the process. Memory allocation data may be collected on one or more host computing devices, the memory allocation data describing the amount of memory allocated for a process or utilized by a process during its execution. The collected memory allocation data may be analyzed to identify instances of anomalous memory allocation during process execution. Statistical or machine learning algorithms may be employed to identify anomalous memory allocation based on the analysis of aggregated memory allocation data for the process.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
| title | Detecting code alteration based on memory allocation |
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